Myocardial infarction is a major cause of death in industrialized countries. Rupture of vulnerable atherosclerotic plaques has been recognized as an important mechanism for an acute myocardial infarction, which may often result in a sudden death. Recent advances in a cardiovascular research have identified structural and compositional features of atherosclerotic plaques that predispose them to rupture. In a majority of vulnerable plaques, these features include a) the presence of activated macrophages at the shoulder or edge of the plaque, b) a thin, unstable fibrous cap and c) a compliant lipid pool. The combination of biochemically initiated weakening, represented by these three features and elevated mechanical stress, may represent a particularly high-risk scenario.
A technique that is capable of detecting plaques vulnerable to rupture may become a valuable tool for guiding management of patients that are at risk, and can assist in the ultimate prevention of acute events. A number of different techniques have been under investigation for the detection of vulnerable plaques. These methods include intravascular ultrasound (“IVUS”), optical coherence tomography (“OCT”), fluorescence spectroscopy, magnetic resonance imaging (“MRI”), computed tomography (“CT”), positron-emission tomography (“PET”) and infrared spectroscopy.
OCT is an imaging technique that can measure an interference between a reference beam of light and a detected beam reflected back from a sample. A detailed system description of conventional time-domain OCT has been provided in Huang et al. “Optical coherence tomography,” Science 254 (5035), 1178-81 (1991). The spectral-domain variant of OCT, called spectral-domain optical coherence tomography (“SD-OCT”), is a technique that is suitable for ultrahigh-resolution ophthalmic imaging. This technique has been described in Cense, B. et al., “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography”, Optics Express, 2004 and in International Patent Publication No. WO 03/062802. In addition, U.S. patent application Ser. No. 10/272,171 filed on Oct. 16, 2002, Wojtkowski et al., “In Vivo Human Retinal Imaging by Fourier Domain Optical Coherence Tomography”, Journal of Biomedical Optics, 2002, 7(3), pp. 457-463, Nassif, N. et al., “In Vivo Human Retinal Imaging by Ultrahigh-Speed Spectral Domain Optical Coherence Tomography”, Optics Letters, 2004, 29(5), pp. 480-482 also relates to this subject matter. In addition, optical frequency domain interferometry (“OFDI”) setup (as described in Yun, S. H. et al., “High-Speed Optical Frequency-Domain Imaging”, Optics Express, 2003, 11(22), pp. 2953-2963, International Publication No. WO 03/062802 and U.S. Patent Application Ser. No. 60/514,769 filed on Oct. 27, 2004 further relate to the subject matter of the present invention.
The SD-OCT and OFDI techniques are similar to the OCT technique in that they provide high-resolution, cross-sectional images of tissue. Such exemplary techniques also enable an accurate characterization of the tissue composition, and provide greatly improved image acquisition rates. These exemplary variants shall be collectively referred to herein as OCT. Of the above-described proposed techniques, OCT technique has been shown to be capable of spatially resolving structural and compositional features thought to be directly responsible for plaque rupture. However, the knowledge of structural and compositional features alone may be insufficient for a detailed understanding and accurate prediction of plaque rupture. A technique that combines structural/compositional information with the measurements of strain and elastic modulus would be preferable.
Certain numerical techniques (e.g., a finite element analysis) have been used for understanding the mechanical stress and strain, and their roles in plaque rupture. Various current analyses have relied upon models of vessel cross-sections based loosely on histology and IVUS, and have obtained either assumed or indirectly measured values for tissue elastic properties. Although these numerical techniques have provided some insight into the plaque rupture, they are disadvantageous because, e.g., a) their accuracy is limited by the imprecise knowledge of the elastic properties and their distribution; and b) they are based on retrospective data, and may not be directly applied to the assessment of the vascular structure in living patients.
IVUS elastography has been developed as a method for measuring the strain in vascular structures in vivo. This exemplary technique may be performed by acquiring multiple, cross-sectional images during a change in intravascular pressure. By correlating these images, the mechanical response of the vessel to the pressure change can be determined resulting in a cross-sectional map of strain, local displacement, deformation, or spatially resolved velocity. Although this technique can be performed in vivo, it provides a low spatial resolution and low contrast between typical tissue components in the atherosclerotic plaques. Further, such technique does not provide the ability to determine the stress independently from the strain, and therefore may not be capable of determining the elastic modulus distributions. OCT elastography technique is based on techniques related to those used in IVUS elastography. The OCT elastography technique can, in principle, provide higher resolution and relative elastic modulus distributions than IVUS elastography. When coupled with knowledge of the pressure load at the arterial lumen, high resolution estimates of absolute elastic moduli are also possible.
Doppler imaging techniques in conjunction with IVUS and OCT have been used for determining the depth-resolved velocity of samples toward or away from an imaging probe. Although several variants of these technologies are known, a common basis is the measurement of the Doppler frequency shift imparted on a probe beam, ultrasound in IVUS and light in OCT, by moving scatterers within the sample.
However, the technique for simultaneously determining structure, composition and biomechanical properties of a sample is not available. This capability would have broad application in biomedicine, but in particular would be effective in detecting the vulnerable plaque and understanding its relationship with acute myocardial infarction.
Further, elastography and modulus imaging techniques generally use estimates of unknown strain or modulus parameters over a number of independent finite elements or image pixels distributed spatially over a region of interest. The higher the used spatial resolution for strain or modulus imaging, the larger the number of independent unknowns that should be estimated. As the parameter space grows, the search for parameter estimates that satisfy the desired objective functional becomes a difficult underdetermined problem. Typically, the number of unknowns far exceeds the number that can be uniquely determined from the underlying imaging data, resulting in many possible solutions satisfying the objective functional. In addition, large computational costs and computing time are generally incurred to probe parameter spaces of high-dimensionality (on the order of >100 dimensions).
Conventional methods for elastography and modulus imaging of biological tissue treat strain or modulus at each finite element or pixel of interest as independent unknowns, typically using a Levenburg-Marquardt or similar algorithm for optimization of the objective functional, as described in A. R. Skovoroda et al., “Tissue elasticity reconstruction based on ultrasonic displacement and strain images”. IEEE Trans Ultrason Ferroelectr Freq Control, Col. 42,1995, pp. 747-765, and F. Kallel et al., “Tissue elasticity reconstruction using linear perturbation method”, IEEE Trans Med Imaging, Vol. 15, 1996, pp. 299-313. To achieve robustness to local minima, multi-resolution methods have been used in which estimates are obtained on a low-resolution grid with fewer unknowns and these low-resolution estimates are then mapped to a higher-resolution grid to initialize parameter optimization in the full-resolution domain. These conventional methods can be time-consuming, requiring several minutes of processing for large regions of interest.